| { | |
| "policy_class": { | |
| ":type:": "<class 'abc.ABCMeta'>", | |
| ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", | |
| "__module__": "stable_baselines3.common.policies", | |
| "__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", | |
| "__init__": "<function ActorCriticPolicy.__init__ at 0x7f58a2cdc3a0>", | |
| "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f58a2cdc430>", | |
| "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f58a2cdc4c0>", | |
| "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f58a2cdc550>", | |
| "_build": "<function ActorCriticPolicy._build at 0x7f58a2cdc5e0>", | |
| "forward": "<function ActorCriticPolicy.forward at 0x7f58a2cdc670>", | |
| "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f58a2cdc700>", | |
| "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f58a2cdc790>", | |
| "_predict": "<function ActorCriticPolicy._predict at 0x7f58a2cdc820>", | |
| "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f58a2cdc8b0>", | |
| "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f58a2cdc940>", | |
| "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f58a2cdc9d0>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc_data object at 0x7f58a2cdb240>" | |
| }, | |
| "verbose": 1, | |
| "policy_kwargs": {}, | |
| "observation_space": { | |
| ":type:": "<class 'gym.spaces.box.Box'>", | |
| ":serialized:": "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", | |
| "dtype": "float32", | |
| "_shape": [ | |
| 8 | |
| ], | |
| "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", | |
| "high": "[inf inf inf inf inf inf inf inf]", | |
| "bounded_below": "[False False False False False False False False]", | |
| "bounded_above": "[False False False False False False False False]", | |
| "_np_random": null | |
| }, | |
| "action_space": { | |
| ":type:": "<class 'gym.spaces.discrete.Discrete'>", | |
| ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", | |
| "n": 4, | |
| "_shape": [], | |
| "dtype": "int64", | |
| "_np_random": null | |
| }, | |
| "n_envs": 1, | |
| "num_timesteps": 200704, | |
| "_total_timesteps": 200000, | |
| "_num_timesteps_at_start": 0, | |
| "seed": null, | |
| "action_noise": null, | |
| "start_time": 1677540292011853199, | |
| "learning_rate": 0.0003, | |
| "tensorboard_log": null, | |
| "lr_schedule": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "_last_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAFqiND5Zejs/6N6YPdW+RL7lB/E8DWzsPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg==" | |
| }, | |
| "_last_episode_starts": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg==" | |
| }, | |
| "_last_original_obs": null, | |
| "_episode_num": 0, | |
| "use_sde": false, | |
| "sde_sample_freq": -1, | |
| "_current_progress_remaining": -0.0035199999999999676, | |
| "ep_info_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "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" | |
| }, | |
| "ep_success_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg==" | |
| }, | |
| "_n_updates": 980, | |
| "n_steps": 2048, | |
| "gamma": 0.99, | |
| "gae_lambda": 0.95, | |
| "ent_coef": 0.0, | |
| "vf_coef": 0.5, | |
| "max_grad_norm": 0.5, | |
| "batch_size": 64, | |
| "n_epochs": 10, | |
| "clip_range": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "clip_range_vf": null, | |
| "normalize_advantage": true, | |
| "target_kl": null | |
| } |